8000 MAINT Make files private for sklearn.metrics and sklearn.metrics.clus… · amueller/scikit-learn@e947689 · GitHub
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NicolasHugglemaitre
NicolasHug
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glemaitre
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MAINT Make files private for sklearn.metrics and sklearn.metrics.cluster (scikit-learn#15306)
1 parent f86e852 commit e947689

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‎.gitignore

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@@ -130,6 +130,18 @@ sklearn/svm/libsvm.py
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sklearn/svm/libsvm_sparse.py
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sklearn/svm/liblinear.py
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sklearn/metrics/cluster/bicluster.py
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sklearn/metrics/cluster/supervised.py
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sklearn/metrics/cluster/unsupervised.py
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sklearn/metrics/cluster/expected_mutual_info_fast.py
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sklearn/metrics/base.py
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sklearn/metrics/classification.py
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sklearn/metrics/regression.py
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sklearn/metrics/ranking.py
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sklearn/metrics/pairwise_fast.py
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sklearn/metrics/scorer.py
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sklearn/inspection/partial_dependence.py
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sklearn/inspection/permutation_importance.py
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‎sklearn/_build_utils/deprecated_modules.py

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'set_verbosity_wrap'),
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('_liblinear', 'sklearn.svm.liblinear', 'sklearn.svm', 'train_wrap'),
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('_bicluster', 'sklearn.metrics.cluster.bicluster',
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'sklearn.metrics.cluster', 'consensus_score'),
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('_supervised', 'sklearn.metrics.cluster.supervised',
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'sklearn.metrics.cluster', 'entropy'),
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('_unsupervised', 'sklearn.metrics.cluster.unsupervised',
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'sklearn.metrics.cluster', 'silhouette_score'),
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('_expected_mutual_info_fast',
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'sklearn.metrics.cluster.expected_mutual_info_fast',
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'sklearn.metrics.cluster', 'expected_mutual_information'),
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('_base', 'sklearn.metrics.base', 'sklearn.metrics', 'combinations'),
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('_classification', 'sklearn.metrics.classification', 'sklearn.metrics',
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'accuracy_score'),
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('_regression', 'sklearn.metrics.regression', 'sklearn.metrics',
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'max_error'),
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('_ranking', 'sklearn.metrics.ranking', 'sklearn.metrics', 'roc_curve'),
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('_pairwise_fast', 'sklearn.metrics.pairwise_fast', 'sklearn.metrics',
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'np'),
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('_scorer', 'sklearn.metrics.scorer', 'sklearn.metrics', 'get_scorer'),
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('_partial_dependence', 'sklearn.inspection.partial_dependence',
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'sklearn.inspection', 'partial_dependence'),
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('_permutation_importance', 'sklearn.inspection.permutation_importance',

‎sklearn/base.py

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@@ -404,7 +404,7 @@ def score(self, X, y, sample_weight=None):
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"""
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from .metrics import r2_score
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from .metrics.regression import _check_reg_targets
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from .metrics._regression import _check_reg_targets
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y_pred = self.predict(X)
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# XXX: Remove the check in 0.23
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y_type, _, _, _ = _check_reg_targets(y, y_pred, None)

‎sklearn/linear_model/ridge.py

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from ..utils.validation import _check_sample_weight
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from ..preprocessing import LabelBinarizer
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from ..model_selection import GridSearchCV
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from ..metrics.scorer import check_scoring
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from ..metrics import check_scoring
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from ..exceptions import ConvergenceWarning
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from ..utils.sparsefuncs import mean_variance_axis
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‎sklearn/metrics/__init__.py

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"""
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from .ranking import auc
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from .ranking import average_precision_score
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from .ranking import coverage_error
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from .ranking import dcg_score
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from .ranking import label_ranking_average_precision_score
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from .ranking import label_ranking_loss
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from .ranking import ndcg_score
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from .ranking import precision_recall_curve
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from .ranking import roc_auc_score
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from .ranking import roc_curve
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from ._ranking import auc
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from ._ranking import average_precision_score
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from ._ranking import coverage_error
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from ._ranking import dcg_score
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from ._ranking import label_ranking_average_precision_score
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from ._ranking import label_ranking_loss
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from ._ranking import ndcg_score
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from ._ranking import precision_recall_curve
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from ._ranking import roc_auc_score
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from ._ranking import roc_curve
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from .classification import accuracy_score
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from .classification import balanced_accuracy_score
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from .classification import classification_report
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from .classification import cohen_kappa_score
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from .classification import confusion_matrix
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from .classification import f1_score
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from .classification import fbeta_score
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from .classification import hamming_loss
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from .classification import hinge_loss
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from .classification import jaccard_similarity_score
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from .classification import jaccard_score
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from .classification import log_loss
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from .classification import matthews_corrcoef
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from .classification import precision_recall_fscore_support
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from .classification import precision_score
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from .classification import recall_score
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from .classification import zero_one_loss
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from .classification import brier_score_loss
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from .classification import multilabel_confusion_matrix
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from ._classification import accuracy_score
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from ._classification import balanced_accuracy_score
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from ._classification import classification_report
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from ._classification import cohen_kappa_score
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from ._classification import confusion_matrix
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from ._classification import f1_score
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from ._classification import fbeta_score
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from ._classification import hamming_loss
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from ._classification import hinge_loss
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from ._classification import jaccard_similarity_score
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from ._classification import jaccard_score
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from ._classification import log_loss
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from ._classification import matthews_corrcoef
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from ._classification import precision_recall_fscore_support
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from ._classification import precision_score
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from ._classification import recall_score
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from ._classification import zero_one_loss
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from ._classification import brier_score_loss
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from ._classification import multilabel_confusion_matrix
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from . import cluster
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from .cluster import adjusted_mutual_info_score
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from .pairwise import pairwise_kernels
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from .pairwise import pairwise_distances_chunked
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from .regression import explained_variance_score
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from .regression import max_error
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from .regression import mean_absolute_error
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from .regression import mean_squared_error
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from .regression import mean_squared_log_error
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from .regression import median_absolute_error
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from .regression import r2_score
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from .regression import mean_tweedie_deviance
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from .regression import mean_poisson_deviance
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from .regression import mean_gamma_deviance
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from ._regression import explained_variance_score
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from ._regression import max_error
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from ._regression import mean_absolute_error
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from ._regression import mean_squared_error
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from ._regression import mean_squared_log_error
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from ._regression import median_absolute_error
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from ._regression import r2_score
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from ._regression import mean_tweedie_deviance
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from ._regression import mean_poisson_deviance
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from ._regression import mean_gamma_deviance
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from .scorer import check_scoring
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from .scorer import make_scorer
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from .scorer import SCORERS
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from .scorer import get_scorer
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from ._scorer import check_scoring
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from ._scorer import make_scorer
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from ._scorer import SCORERS
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from ._scorer import get_scorer
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from ._plot.roc_curve import plot_roc_curve
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from ._plot.roc_curve import RocCurveDisplay

‎sklearn/metrics/base.py renamed to ‎sklearn/metrics/_base.py

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‎sklearn/metrics/classification.py renamed to ‎sklearn/metrics/_classification.py

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‎sklearn/metrics/pairwise_fast.pyx renamed to ‎sklearn/metrics/_pairwise_fast.pyx

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‎sklearn/metrics/ranking.py renamed to ‎sklearn/metrics/_ranking.py

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from ..preprocessing import label_binarize
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from ..preprocessing._label import _encode
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from .base import _average_binary_score, _average_multiclass_ovo_score
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from ._base import _average_binary_score, _average_multiclass_ovo_score
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def auc(x, y):

‎sklearn/metrics/regression.py renamed to ‎sklearn/metrics/_regression.py

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